LuciferYang commented on code in PR #54446:
URL: https://github.com/apache/spark/pull/54446#discussion_r2846439066
##########
mllib/src/test/scala/org/apache/spark/ml/feature/CountVectorizerSuite.scala:
##########
@@ -350,4 +350,18 @@ class CountVectorizerSuite extends MLTest with
DefaultReadWriteTest {
assert(features === Vectors.sparse(0, Seq()))
}
}
+
+ test("SPARK-55655: CountVectorizer vocabulary ordering is deterministic for
tied counts") {
+ val df = Seq(
+ (0, split("a b c d e")),
+ (1, split("e d c b a"))
+ ).toDF("id", "words")
+
+ val cvModel = new CountVectorizer()
+ .setInputCol("words")
+ .setOutputCol("features")
+ .fit(df)
+
+ assert(cvModel.vocabulary === Array("a", "b", "c", "d", "e"))
Review Comment:
cc @zhengruifeng should a stricter ordering be guaranteed here? I
encountered failures caused by this when attempting to upgrade Guava to version
33.5.
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